How systems of operational data analytics are arranged, why multidimensional analysis is more suitable for BI, and what databases are used in OLAP.
Companies’ IT systems usually have applications for complex data analysis. Top management often uses them to make decisions based on data, not on intuition.
To get the information you need to make an informed decision, you need to collect data from various sources and process it. To do this, the corporate data warehouse must be organized uniquely, mainly using OLAP technology. We will consider it in the article.
What Is OLAP, And Why Are Such Systems Needed?
OLAP is online analytical processing, and it is also online data analysis. Let’s try to define this concept in human language.
In IT systems, data is stored in unrelated databases, event storage, files, fast storage, and statistics systems. This heap of information hides what is essential to know for the effective management of an IT product and business. But getting the necessary information from such a heterogeneous structure and presenting it in a form convenient for managers and analysts is problematic.
So engineers came up with systems that keep track of all the data providers themselves and collect everything managers need to know in one place. This is “data analysis.”
Why “operational”? Let’s say you manage a large online store, and right now, you are testing several advertising campaigns for effectiveness. Of all the movements, you need to select the most effective one and work with it further. The data processing system, of course, will allow you to see the correct numbers and make the right decisions. But you need to get the data out of it quickly – if building a report takes weeks, then good choices cannot be made with such a delay.
Therefore, the engineers did not just make a system for processing and analyzing data from heterogeneous sources – they made it fast so that all the necessary information gets to the managers’ desks almost in real-time.
OLAP involves this whole approach and programs engaged in the rapid collection and analysis of information.
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